A Sparse Representation Approach to Online Estimation of Power System Distribution Factors
A Sparse Representation Approach to Online Estimation of Power System Distribution Factors
复制标题
电力系统分布因子在线估计的稀疏表示方法
DOI：
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复制
发表时间：
2015
影响因子：
6.6
通讯作者：
P. Sauer
中科院分区：
文献类型：
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作者：
Y. Chen;A. Domínguez;P. Sauer
在本文中，我们提出了一种方法来计算线性灵敏度分布因子（DF）在接近真实的时间，而不依赖于系统的潮流模型。具体而言，我们计算特定感兴趣线路相对于所有总线处的有功功率注入的注入偏移因子（ISF）（所有其他DF可以从ISF确定）。建议的ISF估计方法依赖于欠定系统的线性方程组的解决方案，所述欠定系统产生于从相量测量单元获得的高频同步测量。我们利用稀疏表示（即，其中许多元素为零），并将估计问题转化为稀疏向量恢复问题。正如我们所示，通过案例研究，所提出的方法提供了准确的DF估计与更少的同步测量比早期的方法，依赖于通过最小二乘误差估计方法的超定方程组的解决方案。
In this paper, we propose a method to compute linear sensitivity distribution factors (DFs) in near real time without relying on a power flow model of the system. Specifically, we compute the injection shift factors (ISFs) of a particular line of interest with respect to active power injections at all buses (all other DFs can be determined from ISFs). The proposed ISF estimation method relies on the solution of an underdetermined system of linear equations that arise from high-frequency synchronized measurements obtained from phasor measurement units. We exploit a sparse representation (i.e., one in which many elements are zero) of the vector of desired ISFs via rearrangement by electrical distance and an appropriately chosen linear transformation, and cast the estimation problem into a sparse vector recovery problem. As we illustrate through case studies, the proposed approach provides accurate DF estimates with fewer sets of synchronized measurements than earlier approaches that rely on the solution of an overdetermined system of equations via the least-squares errors estimation method.